August 2017
Beginner to intermediate
340 pages
8h 42m
English
Content preview from Mastering Machine Learning with Spark 2.x
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Using the super-learner model
The usage of the model is easy-we need to provide a dataset with a single column called reviewText and transform it with superLearnerModel:
val review = "Although I love this movie, I can barely watch it, it is so real....."val reviewToScore= sc.parallelize(Seq(review)).toDF("reviewText")val reviewPrediction= superLearnerModel.transform(reviewToScore)
The returned prediction reviewPrediction is a dataset with the following structure:
reviewPrediction.printSchema()
The first column contains the predicted value, which was decided based on the F1 threshold. The columns p0 and p1 represent probabilities of individual ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.